While customer demand at a power grid distribution network remains relatively predictable during a day, quick morning ramp-ups and late afternoon ramp-downs in grid-connected Renewable Energy Source (RES) power plants without secondary power sources to help demand in a real-time manner pose a severe threat to the stability of the grid and the availability of power to customers. Existing technologies that deal with problems of such magnitude are based on unreliable weather prediction and ineffective modeling, making the overall grid performance unreliable and inefficient.
This necessitates the need for a solution that synergistically integrates novel computational tools for smart RES generation forecasting and wide-area aggregation, optimization for providing dynamic RES hosting capacity, intelligent device synchronization, and on-demand ability to dispatch; complemented by state-of-the-art situationally aware visualization capable of providing in-depth operational visibility for real-time monitoring of the grid with complete accessibility to the entire grid.